Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Acinetobacter baumannii is becoming a gravely threatening nosocomial infection with a higher mortality rate. The present study targets the BaeR protein that mediates resistance to tigecycline antibiotics. The BaeR protein, along with the aid of BaeS, senses the incoming antibiotics and stimulates the expression of resistance proteins. These resistance proteins efflux the antibiotics and protect the cells from its effect. The main goal of the current study is to determine potential inhibitors from already existing FDA-approved drugs that could mitigate the BaeR protein. A range of in silico approaches, including molecular dynamics, virtual screening, SIFT analysis, ADMET, DFT, MM/GBSA, MMPBSA and per residue interaction analysis, were performed to identify inhibitors against this protein. The screening of FDA-approved compounds against the BaeR protein yielded 620 compounds. These compounds were clustered by SIFT to distinguish related compounds, it resulted in 20 different clusters. The top five clusters that can accommodate the binding site with better interaction and score by fulfilling all criteria were selected. The DFT analysis showed a smaller energy gap among all the compounds, indicating the ability of the compound to form firm interactions. All the compounds showed less binding free energy in both MM/GBSA and MM/PBSA analyses. The compounds were observed to be stable throughout the simulation. The per-residue interaction analysis confirmed that interactions with binding site residues were stable throughout the simulation. As a result of the study, four compounds, namely ZINC000003801919, DB01203, DB11217 and ZINC0000000056652, were identified as efficient candidates to deal with antimicrobial resistance in A. baumannii.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1007/s11030-024-10988-5 | DOI Listing |
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